The rationale of the cytokine microarray project

The aim of this project is to develop, apply and adapt DNA
microarray technology for quantitative and kinetic measurements of
cytokine-induced gene expression in cell culture systems, transgenic
mice, animal models of disease and in human patients that are studied
by members of the SFB566.

In the first phase of the project, we decided to design, to produce
and to characterize our own DNA microarrays. To utilize the microarray
in mouse and man a gene list was selected with a maximal overlap of
functionally identical genes. Initially this microarray covered mainly
genes induced during inflammation. To enable many experiments the
microarray had to be produced at low cost; hence we limited the number
of genes initially to about 100 highly regulated inflammatory genes
(including many cytokines and cytokine receptors; see
overview). To keep the microarray versatile and flexible we chose
MWG Biotech's oligonucleotide platform and also established a close
cooperation with MWG Biotech and later with the company Ocimum. To
achieve maximal sensitivity and for highly reproducible results we
chose to design three oligonucleotide probes per gene which were
selected by algorithms developed at MWG Biotech as well as by extensive
data bank comparisons. To validate the probes the microarray was then
tested in a large variety of biological systems in man and mouse and a
strategy was developed to select the best probe per gene (see poster of
our data presented at the International Cytokine Society Meeting 2003
in Dublin gif
349 kB). Final validation of the human and murine probes was
performed
in 214 and 87 hybridizations, respectively. The underlying material for
the validation experiments was derived from the participating projects
of the SFB566 and external collaborators. Altogether more than 25
different cell types (view
list) and more than 30 different stimuli (view
list) were used.

Since 2006, the low density microarray platform was largely replaced
by using the entire Agilent microarray work flow. Price reductions and
the very good performance of their microarrays (see link: Available
microarrays) as well as their accompanying hardware has resulted in the substitution of low density
microarrays by high-density microarrays and by genome-wide analyses of
gene expression in most of our studies. The latter are now being
performed in a highly standardized way on a routine basis.

In addition to providing the basic services of a central microarray
facility, special care is taken to optimize the experimental design of the
individual microarray studies by offering as much advice as possible to
the collaborating research groups. All microarray experiments are
conducted in a highly standardized fashion by our microarray
laboratory. All raw data are thoroughly analyzed, discussed with the
cooperation partners and then stored in a data base (called )
that is accessible via a WEB-based interface to all users. There is
free access to a large set of validation experiments and to many of the already
published microarray experiments. Hence, we have been establishing a
continuously growing repository of mRNA expression data. We have also
explored and utilized multiple ways of visualizing results from data
analyses. This experience has proven to be an indispensable aspect of
our work to assist researchers who use the microarray lab in drawing
meaningful conclusions from their experiments.

Ultimately this data base forms the nucleus to comprehensively
follow the changes in cytokine-networks and cytokine-dependent gene
expression in health and disease. As a long term goal, by
bioinformatics analysis all data will be integrated electronically into
models of cytokine networks and the signaling circuits regulating them.
On the basis of this information key proteins in strategically
prominent locations can then be targeted by RNAi, dominant-negative
mutants, and, eventually, in vivo by genetic strategies developed
within the SFB566 to experimentally perturb the response of targeted
cells and thus verify/modify the circuit model accordingly. The
accuracy of this model will be evaluated further using in vivo models
of cytokine-dependent diseases such as chronic inflammation or
infection.

We also try to collaborate with as many research groups as possible
who work in related areas. We are also interested in obtaining samples
from patients or animal models.